activity
20172022
most citedMemNet: A Persistent Memory Network for Image Restoration

193 citations · 539 across the 28 of their papers we have counts for

collaborators

40 papers

cs.CV20226 cited

IFRNet: Intermediate Feature Refine Network for Efficient Frame Interpolation

Lingtong Kong, Boyuan Jiang, Donghao Luo +5

Prevailing video frame interpolation algorithms, that generate the intermediate frames from consecutive inputs, typically rely on complex model architectures with heavy parameters…

cs.CV20225 cited

FRIH: Fine-grained Region-aware Image Harmonization

Jinlong Peng, Zekun Luo, Liang Liu +6

Image harmonization aims to generate a more realistic appearance of foreground and background for a composite image. Existing methods perform the same harmonization process for the…

cs.CV202214 cited

ASFD: Automatic and Scalable Face Detector

Jian Li, Bin Zhang, Yabiao Wang +6

Along with current multi-scale based detectors, Feature Aggregation and Enhancement (FAE) modules have shown superior performance gains for cutting-edge object detection. However,…

cs.CV20222 cited

CFNet: Learning Correlation Functions for One-Stage Panoptic Segmentation

Yifeng Chen, Wenqing Chu, Fangfang Wang +6

Recently, there is growing attention on one-stage panoptic segmentation methods which aim to segment instances and stuff jointly within a fully convolutional pipeline efficiently.…

cs.CV2022

SCSNet: An Efficient Paradigm for Learning Simultaneously Image Colorization and Super-Resolution

Jiangning Zhang, Chao Xu, Jian Li +4

In the practical application of restoring low-resolution gray-scale images, we generally need to run three separate processes of image colorization, super-resolution, and dows-samp…

cs.CV20217 cited

Spectrum-to-Kernel Translation for Accurate Blind Image Super-Resolution

Guangpin Tao, Xiaozhong Ji, Wenzhuo Wang +6

Deep-learning based Super-Resolution (SR) methods have exhibited promising performance under non-blind setting where blur kernel is known. However, blur kernels of Low-Resolution (…